- From: Waard, Anita de A (ELS-NYC) <A.dewaard@elsevier.com>
- Date: Mon, 6 Feb 2012 13:28:20 +0100
- To: "Nigam Shah" <nigam@stanford.edu>, <gofriends@genome.stanford.edu>, <biopax-discuss@cbio.mskcc.org>, <bfo-discuss@googlegroups.com>, <kr-sig@mailman.amia.org>, <isb@listserv.it.northwestern.edu>, <obo-format@lists.sourceforge.net>, <ncbo-everyone@lists.stanford.edu>, <nlp-sig@mailman.amia.org>, <protege-discussion@lists.stanford.edu>, <public-semweb-lifesci@w3.org>, <bmir-everybody@lists.stanford.edu>, <bmi-students@lists.stanford.edu>, <supd-members@mailman.stanford.edu>, <sbgn-discuss@caltech.edu>, <obo-phenotype@lists.sourceforge.net>
Apologies for cross-postings, Anita de Waard Disruptive Technologies Director, Elsevier Labs http://elsatglabs.com/labs/anita/ a.dewaard@elsevier.com *************************************************** SECOND CALL FOR PAPERS *************************************************** ACL 2012 Workshop on Detecting Structure in Scholarly Discourse, DSSD2012 Web: http://www.nactem.ac.uk/dssd/index.php *************************************************** July 12, 2012 International Convention Center, Jeju Island Republic of Korea *************************************************** Submission deadline: March 11, 2012 *************************************************** The detection of discourse structure in scientific documents is important for a number of tasks, including biocuration efforts, text summarization, error correction, information extraction and the creation of enriched formats for scientific publishing. Currently, many parallel efforts exist to detect a range of discourse elements at different levels of granularity and for different purposes. Discourse elements detected include the statement of facts, claims and hypotheses, the identification of methods and protocols, and as the differentiation between new and existing work. In medical texts, efforts are underway to automatically identify prescription and treatment guidelines, patient characteristics, and to annotate research data. Ambitious long-term goals include the modeling of argumentation and rhetorical structure and more recently narrative structure, by recognizing 'motifs' inspired by folktale analysis. A rich variety of feature classes is used to identify discourse elements, including verb tense/mood/voice, semantic verb class, speculative language or negation, various classes of stance markers, text-structural components, or the location of references. These features are motivated by linguistic inquiry into the detection of subjectivity, opinion, entailment, inference, but also author stance and author disagreement, motif and focus. The goal of the 2012 workshop "Detecting Structure in Scholarly Discourse" is to discuss and compare the techniques and principles applied in these various approaches, to consider ways in which they can complement each other, and to initiate collaborations to develop standards for annotating appropriate levels of discourse, with enhanced accuracy and usefulness. We are inviting submissions of long papers describing original research work that span the range from theory to application, including research on and the practice of manual and automated annotation systems, and discuss questions like the following: . What correlations can be demonstrated among document structure, argumentation and rhetorical functions? . What are the text linguistic and philosophical motivations underpinning current efforts to identify discourse structure? Are the assumptions made by current text processing tools supported by discourse linguistic research; are there unused opportunities for fruitful cross-fertilization? . Can we port parallel efforts from neighboring fields, such as motifs in folktale research, to annotate and detect narrative structures? . Which discourse annotation schemes are the most portable? Can they be applied to both full papers and abstracts? Can they be applied to texts in different domains and different genres (research papers, reviews, patents, etc)? . How can we compare annotations, and how can we decide which features, approaches or techniques work best? What are the most topical use cases? How can we evaluate performance and what are the most appropriate tasks? . What corpora are currently available for comparing and contrasting discourse annotation, and how can we improve and increase these? . How applicable are discourse annotation efforts for improving methods of publishing, detecting and correcting authors' errors at the discourse level, or summarizing scholarly text? How close are we to implementing them at a production scale? Important Dates March 11, 2012 submission deadline April 15, 2012 notification of acceptance April 30, 2012 camera-ready paper July 12, 2012 workshop Submission guidelines: Please use ACL style files listed in http://www.acl2012.org/call/sub01.asp Authors are requested to submit their abstracts at: https://www.softconf.com/acl2012/dssd2012/ Proceedings: The accepted papers will be published in the DSSD2012 Workshop Proceedings Organizing Committee: Sophia Ananiadou, National Centre for Text Mining and University of Manchester Antal van den Bosch, Radboud University Nijmegen Ágnes Sándor, Xerox Research Europe, Grenoble Hagit Shatkay, University of Delaware Anita de Waard, Elsevier Labs/Utrecht University Programme Committee: Catherine Blake, University of Illinois at Urbana-Champaign, USA Kevin Cohen, University of Colorado, School of Medicine, USA Nigel Collier, National Institute of Informatics, Japan Walter Daelemans, University of Antwerp, Belgium Robert Dale, Macquarie University, Australia Kjersti Fløttum, University of Bergen, Norway Rocana Girju, University of Illinois at Urbana-Champaign, USA Lynette Hirschman, MITRE, USA Halil Kilicoglu, Concordia University, Canada Jin-Dong Kim, The University Of Tokyo, Japan Anna Korhonen, Cambridge University, UK Maria Liakata, Aberystwyth University, UK Roser Morante, University of Antwerp, Belgium Raheel Nawaz, University of Manchester, UK Dragomir Radev, University of Michigan, USA Dietrich Rebholz-Schuhmann, EBI, UK Andrey Rzhetsky, University of Chicago, USA Caroline Sporleder, Saarland University, Germany Padmini Srinivasan, University of Iowa, USA Simone Teufel, University of Cambridge, UK Paul Thompson, University of Manchester, UK Jun'ichi Tsujii, Microsoft Research Asia, China Lucy Vanderwende, Microsoft Research, USA Contact: Anita de Waard Disruptive Technologies Director, Elsevier Labs http://elsatglabs.com/labs/anita/ a.dewaard@elsevier.com Elsevier B.V. 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Received on Monday, 6 February 2012 12:51:24 UTC